code: def build_table(d):
      lines = list()
      for est in d.keys():
          sum_ = 0
          t_list = list(
              [
                  est.replace("_", " "),
              ]
          )
          for t in (CAT, CONT):
              sum_ += d[est][t]
              t_list.append("%d (%d)" % (d[est][t], d[est][COND][t]))
          t_list.append("%d" % d[est][CONST])
          t_list.append("%d" % d[est][UN])
          sum_ += d[est][CONST] + d[est][UN]
          t_list.insert(1, "%d" % sum_)
          lines.append(" & ".join(t_list))
      return "\\\\ \n".join(lines)
  
file_path: auto-sklearn/misc/create_hyperparameter_table.py
imports: from argparse import ArgumentParser
  from collections import OrderedDict
  import os
  import shlex
  import subprocess
  import ConfigSpace.hyperparameters
  import autosklearn.pipeline.classification
  import autosklearn.pipeline.regression
label_desc: Use image node_id 2 for calling a global function with example usage: build_table(d) and returns: str